Clustering user queries into conceptual space
Li-Chin Lee, Yi-Shin Chen · 2013
The gap between user search intent and search results is an important issue. Grouping terms according to semantics seems to be a good way of bridging the semantic gap between the user and the search engine. We propose a framework to extract semantic concepts by grouping queries using a clustering technique. To represent and discover the semantics of a query, we utilize a web directory and social annotations (tags). In addition, we build hierarchies among concepts by splitting and merging clusters iteratively. Exploiting expert wisdom from web taxonomy and crowd wisdom from collaborative folksonomy, the experiment results show that our framework is effective.